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Soil moisture decorrelation timescales are sensitive to precipitation variability and land-atmosphere coupling.

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Title: Soil moisture decorrelation timescales are sensitive to precipitation variability and land-atmosphere coupling.
Authors: Maruf, Montasir1 (AUTHOR), Kumar, Sanjiv1 (AUTHOR) szk0139@auburn.edu
Source: Journal of Hydrometeorology. May2026, Vol. 27 Issue 5, p1-22. 22p.
Subjects: Precipitation variability, Land-atmosphere interactions, Atmospheric models, Timescale number, Soil moisture
Abstract: This study investigates soil moisture decorrelation timescales, commonly referred to as soil moisture memory, by examining their sensitivity to meteorological forcing, specifically autocorrelation structure in precipitation data and land-atmosphere coupling using the Community Land Model version 5 (CLM5). We conduct CLM5 experiments using two widely used meteorological datasets: the Climate Forecast System Reanalysis (CFSR) and the Global Soil Wetness Project phase 3 (GSWP3), along with randomized meteorological forcing to isolate the role of climate variability and persistence on soil moisture decorrelation timescales. Results show that the CFSR-forced CLM5 simulation yields decorrelation timescales that are, on average, twice as high as those from the GSWP3-forced simulation, particularly in tropical and subtropical regions, due to significant precipitation autocorrelation and enhanced soil moisture–precipitation feedback in the CFSR case. Randomized meteorological forcing significantly reduces decorrelation timescales in CFSR-forced CLM5 simulations (by 50–70%) but only marginally in GSWP3-forced simulations (by 10–20%). Additional analysis using the drydown timescale metric reveals minimal differences between CFSR- and GSWP3-forced simulations, highlighting the dependency of findings on the memory metrics and the role of land surface hydrologic processes. Comparisons with CESM2 Large Ensemble (CESM2-LE) reveal that a fully coupled model underestimates the decorrelation timescales relative to the CFSR-forced CLM5 simulation and aligns more closely with the GSWP3-forced CLM5 simulation. Soil moisture reemergence, identified as a secondary autocorrelation peak, disappears under randomized forcing, indicating its dependence on climate variability rather than solely on land surface processes. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Hydrometeorology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Label: Title
  Group: Ti
  Data: Soil moisture decorrelation timescales are sensitive to precipitation variability and land-atmosphere coupling.
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  Data: <searchLink fieldCode="AR" term="%22Maruf%2C+Montasir%22">Maruf, Montasir</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kumar%2C+Sanjiv%22">Kumar, Sanjiv</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> szk0139@auburn.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Hydrometeorology%22">Journal of Hydrometeorology</searchLink>. May2026, Vol. 27 Issue 5, p1-22. 22p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Precipitation+variability%22">Precipitation variability</searchLink><br /><searchLink fieldCode="DE" term="%22Land-atmosphere+interactions%22">Land-atmosphere interactions</searchLink><br /><searchLink fieldCode="DE" term="%22Atmospheric+models%22">Atmospheric models</searchLink><br /><searchLink fieldCode="DE" term="%22Timescale+number%22">Timescale number</searchLink><br /><searchLink fieldCode="DE" term="%22Soil+moisture%22">Soil moisture</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study investigates soil moisture decorrelation timescales, commonly referred to as soil moisture memory, by examining their sensitivity to meteorological forcing, specifically autocorrelation structure in precipitation data and land-atmosphere coupling using the Community Land Model version 5 (CLM5). We conduct CLM5 experiments using two widely used meteorological datasets: the Climate Forecast System Reanalysis (CFSR) and the Global Soil Wetness Project phase 3 (GSWP3), along with randomized meteorological forcing to isolate the role of climate variability and persistence on soil moisture decorrelation timescales. Results show that the CFSR-forced CLM5 simulation yields decorrelation timescales that are, on average, twice as high as those from the GSWP3-forced simulation, particularly in tropical and subtropical regions, due to significant precipitation autocorrelation and enhanced soil moisture–precipitation feedback in the CFSR case. Randomized meteorological forcing significantly reduces decorrelation timescales in CFSR-forced CLM5 simulations (by 50–70%) but only marginally in GSWP3-forced simulations (by 10–20%). Additional analysis using the drydown timescale metric reveals minimal differences between CFSR- and GSWP3-forced simulations, highlighting the dependency of findings on the memory metrics and the role of land surface hydrologic processes. Comparisons with CESM2 Large Ensemble (CESM2-LE) reveal that a fully coupled model underestimates the decorrelation timescales relative to the CFSR-forced CLM5 simulation and aligns more closely with the GSWP3-forced CLM5 simulation. Soil moisture reemergence, identified as a secondary autocorrelation peak, disappears under randomized forcing, indicating its dependence on climate variability rather than solely on land surface processes. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Hydrometeorology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1175/JHM-D-25-0062.1
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 22
        StartPage: 1
    Subjects:
      – SubjectFull: Precipitation variability
        Type: general
      – SubjectFull: Land-atmosphere interactions
        Type: general
      – SubjectFull: Atmospheric models
        Type: general
      – SubjectFull: Timescale number
        Type: general
      – SubjectFull: Soil moisture
        Type: general
    Titles:
      – TitleFull: Soil moisture decorrelation timescales are sensitive to precipitation variability and land-atmosphere coupling.
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            NameFull: Maruf, Montasir
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          Name:
            NameFull: Kumar, Sanjiv
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            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
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              Value: 1525755X
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              Value: 27
            – Type: issue
              Value: 5
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            – TitleFull: Journal of Hydrometeorology
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